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To enhance the robustness of the vehicle detection system, an effective algorithm to identify the lighting conditions (daylight, night, lowlight (dawn, dusk)) based on histogram analysis is presented in this paper. The algorithm consists of two procedures: extracting and updating background image, and generating a lighting conditions classifier based on background image analysis. The algorithm is...
Real-time image processing is a difficult work for traffic video monitoring. This paper proposed a method to detect and track vehicles on highway based on airship video and therefore calculate traffic parameters in real-time. A blocking road extraction was performed to determine the ROI, and automatically calculate the tilt of the road which contributes to vehicles detection. A lane marks registration...
In modern intelligent transportation systems, the video image vehicle detection system (VIVDS) is gradually becoming one of the popular methods at signalized traffic intersection due to its convenient installation and rich information content provided. However, in the current VIVDS, the camera usually is installed at the roadside poles or traffic light poles, which not only requires more than one...
Developing real-time traffic parameters surveillance systems based on video aiming to extract reliable traffic state information has attracted a lot of attention during the past decades. These traffic state parameters include traffic flow density, the length of queue, average traffic speed and total vehicle in fixed time intervals. In these systems, robust and reliable vehicle detection and tracking...
The problem of vehicle detection and segmentation in outdoor scenes is tackled. Vehicle shadows pose problems in vehicle segmentation step. In this paper, it is proposed to employ temporal edge density information as prior knowledge to distinguish moving vehicle from moving shadow and background in a traffic surveillance system. Experimental results showed good moving vehicle segmentation performance...
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